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Module Overview

Data Management

No enterprise can be effective without high quality data. Today’s organisations rely on their data assets to make more informed and more effective decisions. Leading organisations are using their data assets to create competitive advantages through greater knowledge of their customers, ethical and innovative uses of information and operational efficiencies.

Data is becoming a valuable asset for companies but the management of data is subject to huge challenges including meeting data regulatory, legal and governance requirements, maintaining data privacy and ensuring the quality of the data throughout the data lifecycle and over time. 

The aim of this module is to analyse and evaluate the role of data management in an organisation and the various roles, ethical theories and frameworks, processes, tools, techniques, requirements etc. that are involved in the data management function. 

Module Code

DATA 9911

ECTS Credits

5

*Curricular information is subject to change

Module content will be broadly as follows:

  • Introduction/ Overview
    • Data governance
    • Data management roles & responsibilities
    • Legal & regulatory issues for the storage and management of data, e.g GDPR  (just a note. the legal&ethical aspects of analytics and ML in GDPR etc is covered in Data Mining)
    • Shared and open data
    • Data privacy and security issues

 

  • Data Management
    • The Chief Data Office and the Data Controller
    • Data roles and responsibilities
    • Key data stakeholders
    • Data stewardship in organisations
    • Data Management Plans (for academic and industry research)
    • Data Protection Impact Assessment

 

  • Types of data, the data lifecycle, the data pipeline
    • Typical Data Types, structured, unstructured, metadata, etc...
    • Data sourcing and capture, data provenance
    • Impact of evolutionary technology on data e.g. IoT, conversational devices, automated data generation, etc
    • Handling concept drift in data
    • The data pipeline, DataOps

 

  • Data Quality
    • Data quality dimensions
    • Data quality measurement
    • Data accuracy
    • Data quality improvement

 

  • Ethics and Bias in Data
    • An ethical view on data use in the modern world
    • Impact of bias on data driven decision processes
    • Measuring bias in data
    • Mitigating bias in data

 

  • Data Law and Regulation
    • Historic regulation and the need for GDPR
    • GDPR roles
    • GDPR rights
    • GDPR responsibilities
    • Case studies of the impact of GDPR on various organisation types

 

  • Data Security & Privacy
    • Data storage
    • Organisational policy on data control and data breaches
    • Privacy management
    • Anonymisation and pseudo-anonymisation for data

 

 

The module is designed to be delivered within a blended learning model, employing mixed modes (online and face to face) of learning, teaching and assessment.

TU059 will be delivered primarily in a face-to-face mode while TU060 will be delivered in a blended mode.

This module will be presented over 13 lectures, and copies of the lecture material will be provided.  Students will be expected to use library and internet based information sources extensively, and familiarise themselves with the supplemental reading. They will be encouraged to be pro-active in their approach to learning.

The continuous assessment will take the form of case studies, reports and presentations. Students will be required to work both independently and as part of groups. Where possible real world examples will be used.

Students will also be strongly encouraged to engage with various websites and discussion forums from organisations, research groups and conferences supporting this topic area. Examples include Data Management Association (DAMA), Data Protection Forum, Data Governance & Information Quality Conference, etc.

 
Module Content & Assessment
Assessment Breakdown %
Other Assessment(s)100